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地铁齿轮箱振动情况复杂,微弱故障特征常被噪声湮没而难以提取。本文提出一种改进的EMDBSS算法,通过计算IMF分量的相关系数矩阵,优化单通道EMD-BSS方法中的IMF信号重组过程,并对重组后的信号进行微弱故障特征提取。将该算法应用于仿真信号及实测地铁齿轮箱轴承故障振动信号中,成功提取出微弱故障特征,验证了算法的有效性。该算法的提出对于单通道微弱故障特征提取具有积极意义。
Subway gearbox vibration situation is complex, weak fault characteristics often annihilated by noise and difficult to extract. In this paper, an improved EMDBSS algorithm is proposed. By calculating the correlation coefficient matrix of IMF components, the IMF signal recombination process in single-channel EMD-BSS method is optimized and the weak fault feature is extracted. The algorithm is applied to the simulation signal and the measured vibration signal of the metro gearbox bearing fault, and the weak fault feature is successfully extracted, which verifies the effectiveness of the algorithm. The proposed algorithm is of positive significance for single-channel weak fault feature extraction.